Ant lion optimizer: theory, literature review, and application in multi-layer perceptron neural networks
This chapter proposes an efficient hybrid training technique (ALOMLP) based on the Ant
Lion Optimizer (ALO) to be utilized in dealing with Multi-Layer Perceptrons (MLPs) neural …
Lion Optimizer (ALO) to be utilized in dealing with Multi-Layer Perceptrons (MLPs) neural …
Hybrid approaches to optimization and machine learning methods: a systematic literature review
Notably, real problems are increasingly complex and require sophisticated models and
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
Classification assessment methods
A Tharwat - Applied computing and informatics, 2021 - emerald.com
Classification techniques have been applied to many applications in various fields of
sciences. There are several ways of evaluating classification algorithms. The analysis of …
sciences. There are several ways of evaluating classification algorithms. The analysis of …
Multi-population differential evolution-assisted Harris hawks optimization: Framework and case studies
The first powerful variant of the Harris hawks optimization (HHO) is proposed in this work.
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …
An enhanced bacterial foraging optimization and its application for training kernel extreme learning machine
H Chen, Q Zhang, J Luo, Y Xu, X Zhang - Applied Soft Computing, 2020 - Elsevier
Abstract The Bacterial Foraging Optimization (BFO) algorithm is a swarm intelligent
algorithm widely used in various optimization problems. However, BFO suffers from multiple …
algorithm widely used in various optimization problems. However, BFO suffers from multiple …
Chaotic vortex search algorithm: metaheuristic algorithm for feature selection
Abstract The Vortex Search Algorithm (VSA) is a meta-heuristic algorithm that has been
inspired by the vortex phenomenon proposed by Dogan and Olmez in 2015. Like other meta …
inspired by the vortex phenomenon proposed by Dogan and Olmez in 2015. Like other meta …
Chaotic dragonfly algorithm: an improved metaheuristic algorithm for feature selection
Selecting the most discriminative features is a challenging problem in many applications.
Bio-inspired optimization algorithms have been widely applied to solve many optimization …
Bio-inspired optimization algorithms have been widely applied to solve many optimization …
Cqffa: A chaotic quasi-oppositional farmland fertility algorithm for solving engineering optimization problems
Abstract Farmland Fertility Algorithm (FFA) is a recent nature-inspired metaheuristic
algorithm for solving optimization problems. Nevertheless, FFA has some drawbacks: slow …
algorithm for solving optimization problems. Nevertheless, FFA has some drawbacks: slow …
Support vector regression optimized by meta-heuristic algorithms for daily streamflow prediction
Accurate and reliable prediction of streamflow is vital to the optimization of water resources
management, reservoir flood operations, catchment, and urban water management. In this …
management, reservoir flood operations, catchment, and urban water management. In this …
Parameter investigation of support vector machine classifier with kernel functions
A Tharwat - Knowledge and Information Systems, 2019 - Springer
Support vector machine (SVM) is one of the well-known learning algorithms for classification
and regression problems. SVM parameters such as kernel parameters and penalty …
and regression problems. SVM parameters such as kernel parameters and penalty …